@InProceedings{li-zhang-li:2017:SIGHAN-9,
  author    = {Li, Shuihua  and  Zhang, Xiaoming  and  Li, Zhoujun},
  title     = {Chinese Answer Extraction Based on POS Tree and Genetic Algorithm},
  booktitle = {Proceedings of the 9th SIGHAN Workshop on Chinese Language Processing},
  month     = {December},
  year      = {2017},
  address   = {Taiwan},
  publisher = {Association for Computational Linguistics},
  pages     = {30--36},
  abstract  = {Answer extraction is the most important part of a chinese web-based question
	answering system. In order to enhance the robustness and adaptability of answer
	extraction to new domains and eliminate the influence of the incomplete and
	noisy search snippets, we propose two new answer exraction methods. We utilize
	text patterns to generate Part-of-Speech (POS) patterns. In addition, a method
	is proposed to construct a POS tree by using these POS patterns. The POS tree
	is useful to candidate answer extraction of web-based question answering. To
	retrieve a efficient POS tree, the similarities between questions are used to
	select the question-answer pairs whose questions are similar to the unanswered
	question. Then, the POS tree is improved based on these question-answer pairs.
	In order to rank these candidate answers, the weights of the leaf nodes of the
	POS tree are calculated using a heuristic method. Moreover, the Genetic
	Algorithm (GA) is used to train the weights. The experimental results of
	10-fold crossvalidation show that the weighted POS tree trained by GA can
	improve the accu-
	racy of answer extraction.},
  url       = {http://www.aclweb.org/anthology/W17-6004}
}